WANG Zaichuang,GUO Mingyang,LIU Bin,et al.Electric power trading model between shared energy storage and active energy participant based on strategic double auction mechanism[J].Electric Power Automation Equipment,2026,46(03):41-50.
WANG Zaichuang,GUO Mingyang,LIU Bin,et al.Electric power trading model between shared energy storage and active energy participant based on strategic double auction mechanism[J].Electric Power Automation Equipment,2026,46(03):41-50. DOI: 10.16081/j.epae.202507017.
Electric power trading model between shared energy storage and active energy participant based on strategic double auction mechanism
To enhance the energy trading efficiency among active energy participants,a new community energy trading system for active energy participants based on shared energy storage is constructed. The system transforms the energy trading among active energy participants into the transactions with shared energy sto-rage devices and achieves the optimal energy matching among active energy participants based on a strategic double auction mechanism. An energy trading framework for active energy participants and shared energy storage devices is constructed,and the energy trading is divided into direct trading and buffer trading. A two-stage energy trading model for active energy participants and shared energy storage devices is established based on the double auction mechanism. In stage 1,based on the predicted data,the day-ahead optimization is carried out with the goals of maximizing the revenue of shared energy storage and minimizing the energy consumption cost of active energy participants,and the bidding information is reported. In stage 2,for the real-time market,the winning bid information is adjusted with the goal of maximizing the utility of each participant,and the bidding equilibrium is achieved through price iteration. Based on the real-time equilibrium bidding information,the winning bid resources are allocated by using the equal-sharing method. The effectiveness of the proposed model and method is verified by the simulative results of example. The results show that,the proposed method can smooth the net load fluctuation of the community. Compared with the experience-based bidding method,the winning bid rate is increased by 1 %,the average energy consumption cost of active energy participants is reduced by 2.9 %,and the revenue of energy storage is increased by 15.8 %.
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